System and method for assessing operational process risk and quality by calculating operational value at risk

ABSTRACT

Methods and apparatus for assessing operational process quality and risk of an entity or a group of entities. The present invention enables a user to effectively compare one or more events, representing what actually happened, with a reference, which represents ideal performance in terms of operational process quality and risk, and express the corresponding results in quantitative terms. The present invention is capable of presenting results in a form and with sufficient rapidity that a human decision-maker is able to timely observe conditions which represent unacceptable quality or excessive risk and respond appropriately.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention relates generally to the field of process qualityand risk assessment and, more specifically, to operational processquality and risk assessment in connection with financial services, andinvestment management organizations.

2. Background Information

Businesses which provide financial or investment management services aresubject to a wide range of legal requirements which apply to theiroperational processes. Such requirements, which are typically statutory,regulatory or contractual in nature, govern or impact most aspects ofthe operations of such businesses. While some of these requirements areapplicable to the business as a whole, many of them are applicable atthe level of a single account holder or single account.

Under ideal conditions, a business should be in compliance with alllegal requirements at all times. However, in a large enterprise which ismaintaining hundreds of is thousands or millions of accounts, andprocessing tens or hundreds of millions of transactions, it isforeseeable that good faith mistakes will occur which represent at leasttechnical violations of one or more legal requirements. Of course, thereis also the possibility of deliberate wrongdoing which results in aviolation of a legal requirement and may constitute a crime.

Regardless of the underlying cause of a failure to comply with a legalrequirement, the business may face substantial liability to aggrievedaccount holders or other businesses which are parties to particulartransactions. In addition, regulatory agencies may assess sanctions. Toavoid or at least minimize the possibility of such liability, a businessneeds to know, at a given point in time or over a selected time period,to what degree it is in compliance with pertinent legal requirements.Stated another way, a business needs a capability to assess itsoperational process quality and risk.

SUMMARY OF THE INVENTION

In brief summary, the present invention provides methods and apparatusfor assessing operational process quality and risk of an entity or agroup of entities. The present invention enables a user to effectivelycompare one or more events (what actually happened) with a reference(what was supposed to happen), which represents ideal performance interms of operational process quality and risk, and express thecorresponding results in quantitative terms. The present invention iscapable of presenting results in a form and with sufficient rapiditythat a human decision-maker is able to timely observe conditions whichrepresent unacceptable quality or excessive risk and respondappropriately.

The present invention provides a system interface through which eventsand other data are gathered from selected sources; a database or otherdata structure in which event, reference information or other data arestored; a library of operational process quality and risk metrics whichmay be selected by a user and applied to a specified set of data in thedata store; and a user interface through which results are displayed toa user and through which a user may specify inquiries that are ofinterest.

In one aspect of the invention, events are logged to the data storebased on a predefined time period and resolution for a given entity.Selected reference metrics and operational process quality and riskmetrics are then applied to the event data to calculate the operationalvalue at risk for the predefined time period and resolution for thegiven entity. In addition, event data in the data store may bedynamically aggregated to effectively represent larger time periods,larger time resolutions and groups of entities.

The present invention may be advantageously used in a wide variety ofways. For example, the present invention may be used to assess andmonitor the aggregate operational risk associated with failing to complywith regulatory, contractual or other expectations attached totransactions involving the movement or exchange of cash, securities,assets or liabilities. A brokerage firm, investment management firm,hedge fund, mutual fund firm or other type of financial servicesorganization may use the present invention to monitor operational risk,essentially in real-time, at any desired resolution ranging from anindividual customer's single account or group of accounts, to an entiremutual fund, or the organization as a whole.

In similar fashion, the present invention may be used to assess orcompare the performances, in terms of operational risk, of differentbusiness units or different organizations and their respectiveoperational practices. The results of such comparisons may be used tomeasure and attribute operations performance, to identify and prioritizeoperational and system improvement opportunities, to calculate operatingrisk capital allocations or reserves to establish premiums or benchmarksfor insurance underwriting purposes, to distribute performance-basedcompensation or any of a number of other purposes.

BRIEF DESCRIPTION OF THE DRAWINGS

The invention description below refers to the accompanying drawings, ofwhich:

FIG. 1 is a block diagram of an apparatus for assessing operationalprocess quality and risk constructed in accordance with a preferredembodiment of the present invention;

FIG. 2 is a simplified diagram of records in a database which may beused to implement various stores shown in FIG. 1;

FIG. 3 is a block diagram illustrating a high level softwarearchitecture for the apparatus of FIG. 1;

FIG. 4 is a flowchart showing an exemplary method for using theapparatus of FIG. 1 to assess operational process quality and risk; and

FIG. 5 is a block diagram illustrating the relationships among activeparticipant firms and interested party firms to a common event.

DETAILED DESCRIPTION OF AN ILLUSTRATIVE EMBODIMENT

As used in the specification and claims herein, the italicized terms aredefined as follows:

entity means a natural person, account or any organization which holds alegal, beneficial, contractual, regulatory or other interest in orobligation with respect to a financial instrument;

financial instrument means cash, a security, an asset or a liability;

event means an action, transaction or omission with respect to afinancial instrument that affects the value of an entity;

basis point means a quantitative expression of financial risk associatedwith one or more events;

process means one or more events which follow from or are necessary toinitiate, sustain, maintain or terminate a legal, beneficial,contractual, regulatory or other interest or obligation in a financialinstrument;

process measure means one or more logical expressions used to calculateoperational process quality and risk metric;

metric includes a factor, dimension or other indicator of operationalprocess quality or risk;

rule means one or more logical expressions which represent an express,implied or mandated legal requirement or other expectation;

factor means a quantitative expression which has a known relationship toan entity; and

dimension means a selected combination of factors that provides a viewof a process.

FIG. 1 shows in block diagram form a system 2 for assessing operationalprocess quality and risk in a financial or investment managementservices business. As used herein, unless otherwise indicated, the terms“operational process quality” and “operational process risk” are usedinterchangeably. A user interface 4 is coupled to a store 6 whichcontains derived metrics. A process measures/rules store 8 is alsocoupled to derived metrics store 6. A data store 10, which is coupled toprocess measures/rules store 8, is arranged to receive and storeexternal application data 12 and manually input data 14 which representevents.

In general, system 2 may be implemented in the form of a softwareapplication which runs on conventional computer hardware as either astandalone application or within a client/server environment. Forexample, user interface 4 may be implemented in the form of a graphicaluser interface (GUI) through which a user, employing a conventionalkeyboard, mouse or other device, may enter data or commands, manipulatea display, print and the like. In general, derived metrics store 6,process measures/rules store 8 and data store 10 may be implementedusing conventional computer memory (RAM), a hard disk or other massstorage media (or a combination thereof) along with conventionaldatabase software or other conventional software.

The overall operation of system 2 will now be described. Metrics store 6contains one or more metrics which pertain to a process for which a userwishes to assess the quality and risk. For example, a metric forassessing the quality and risk of managing a brokerage account is theelapsed time between when a trade is executed and settlement.

Process measures/rules store 8 contains one or more rules which pertainto the process of interest to the user. In the brokerage accountcontext, an example of a rule is that a trade of a security must besettled on the third business day after the trade was executed.

Data store 10 is used to store information regarding entities, eventsand financial instruments which are related to the process for which auser wishes to assess the quality and risk. The information contained indata store 10 may be obtained from sources which are external to system2 (e.g., transactions posted to an account) or may be input manually bythe user or both.

In general, through interaction with user interface 4, a user may assessoperational process quality or risk in the following manner. The userselects at least one metric of interest. Certain process measures/rules,contained in store 8, which pertain to the selected metric are appliedto selected event data contained in data store 10. Event data may beselected based upon user-specified criteria such as time period, entityor entities of interest and the like. Event data may also be selectedautomatically.

The application of process measures/rules, which represent what wassupposed to happen under ideal conditions, to selected event data, whichrepresent what actually happened, produces intermediate results whichare passed to the selected metric. Based on the intermediate results, aprocess metric calculates an operational value at risk metric expressedin basis points. The expression of operational risk in basis pointsprovides at least two significant advantages. First, a basis point is aquantitative unit that is familiar to and generally understood bypersons in the fields of financial and investment management services.Second, the expression of operational risk in this fashion becomes aninstantly recognizable warning: the larger the magnitude, the greaterthe risk (or lower the quality).

FIG. 2 shows examples of records which may be used to organizeinformation contained in stores 6, 8 and 10 of FIG. 1. An event record16 may be used to organize information related to events in the form ofdatabase records contained in data store 10. Each event record 16includes an event identifier 18, an entity identifier 20, a financialinstrument identifier 22, an event type 24, one or more expectedconditions 26, one or more actual conditions 28, a value 30 and one ormore categories 32.

Event identifier 18 comprises a number or other information which servesas a unique identifier of a particular event. Entity identifier 20comprises a number or other information which serves as a uniqueidentifier of a particular entity or possibly a group of entities.Similarly, financial instrument identifier 22 comprises a number orother information which uniquely identifies a particular financialinstrument to which the identified event relates. Each expectedcondition 26 represents something which, under normal circumstances,should occur in connection the identified event while each actualcondition 28 represents what did occur. Value 30 comprises a number orother information which represents value of the identified financialinstrument. Each category 32 may represent an asset type, geographiclocation, portfolio type or other characteristic of interest.

A factor record 34 may be used to organize information related tofactors in the form of database records contained in metrics store 6.Each factor record 34 includes a factor identifier 36 which comprises anumber or other information that serves as a unique identifier of aparticular factor. Each factor record also includes one or more values38 a-38 e which correspond, respectively, to the value of the factor atdifferent points in time T1, T2 . . . TN. Similarly, a dimension record40 includes a dimension identifier 42, which is used to uniquelyidentify a dimension, as well as values 44 a-44 e which correspond,respectively, to the value of the dimension at different points in timeT1, T2 . . . TN.

A rule record 46 may be used to organize information related to rules inthe form of database records contained in process measures/rules store8. Each rule record includes a rule identifier 48, an entity identifier50, a financial instrument identifier 52, a rule type 54 and one or moreconditions 56 a-56 b which correspond, respectively, to conditions 1 . .. N. Rule identifier 48 comprises a number or other information thatserves as a unique identifier of a particular rule. Entity identifier 50and financial instrument identifier 52 are comparable to identifiers 20and 22, respectively, discussed above. Rule type 54 comprises a numberor other information which characterizes the nature of the rule (e.g.,contractual, regulatory, express, implied, etc.). Each of conditions 56represents something which is required to be done in connection with theidentified rule.

FIG. 3 shows a series of process modules which when used togetherprovide a method for using the apparatus of FIG. 1 to assess operationalprocess quality and risk. An input storage module 58 contains or hasaccess to both process measures/rules contained within processmeasures/rules store 8 and data regarding entities, events and financialinstruments contained within data store 10. Pertinent data and rules aresupplied to a processing module 64 which functions to derive factor anddimensions which are useful for quality or risk assessment of a processof interest. Metric storage module 60 contains or has access to thederived factors and dimensions as well as their respective histories.

In module 66, factors and dimensions of interest are calculated (i.e., aquantitative value is calculated at one or more points in time), theresults summarized and formatted as appropriate before being passed to apresentation module 62. Presentation module 62 is responsible fordisplaying the results as a screen presentation 65 or other devicepresentation 68.

FIG. 4 is a flowchart illustrating a method of assessing operationalprocess quality and risk using the system of FIG. 1. At step 70, datarepresenting one or more events is selected by a user. At step 72, oneor more rules, appropriate to the entity, event or financial instrumentassociated with the event chosen in the operational process of interest,is applied to the data selected in step 70. At step 74, a determinationis made as to the degree to which the actual operational process,evidenced by the events, complied with the applicable rule or rules. Theoutcome of the determination will be that the event analyzed eithercomplies with the requirement represented by the rule (or rules) or itdoes not. The results of the determination made at step 74 are used atstep 76 to cumulate the results for the chosen time period intogroupings of compliant/non-compliant quantity performance and riskmetrics by event into factors, dimensions and indexes that representmeasures of operating performance and risk. These results are aggregatedand sorted and the results are displayed to a user at step 80 as ameasurement view for the time period of interest (i.e., a graphicaldisplay of operational process quality and risk at a moment in time).The method may be used to represent a static time period or may beupdated continuously as new events become known to the methods analysisand comparison process or apparatus.

The results of the determination made at step 74 are also, at step 78,added to a time sequence data store, which serves to aggregate results.The application of the compliant/non-compliant metrics to the timesequence data store are displayed to a user at step 82 as a timesequenced measurement view (i.e., a graphical display of operationalprocess quality and risk over a period of time which may be selected orvaried by the user).

Some examples of how the apparatus and methods described above may beused to assess operational process quality and risk will now bedescribed. An example of the practical risk and quality metrics includethe measurement of process performance of the financial instrument tradesettlement process based on the measured value at risk as a result of anon-compliant trade event. An investment firm might wish to determinethe value at risk in its operational process resulting from the failureto appropriately record each and every trade settlement event on thecontractual settlement date established for the specific event. Thiscontractual rule would be used to test each trade settlement event bycomparing the posting date-time stamp data element recorded, for thespecific trade settlement event, with the contractual settlement datedata element established for the specific trade settlement event todetermine whether the event is compliant or non-compliant with thecontractual rule.

If an event is non-compliant with the contractual rule, the tradesettlement dollar-value data element recorded for the specific tradesettlement event may be divided by the total value of all the tradesettlement events with the same user specified time period orcontractual settlement date. The resultant value for the specificnon-compliant event may then be expressed as a basis point value fordisplay to a user. Further, the total value of all non-compliant eventsmay be divided by the total value of all the trade settlement eventswith the same contractual settlement date and the resultant value forall non-compliant events expressed as a basis point value.

In another example, a bank might wish to determine the quality in itscash wire-transfer deposit operational process resulting from thefailure to appropriately record each and every cash wire-transferdeposit into a beneficiary account on the contractual funds-availabilitydate established for the specific cash wire-transfer deposit event. Thiscontractual rule would be used to test each cash wire-transfer depositinto a beneficiary account by comparing the posting date-time stamp dataelement recorded for the specific cash wire-transfer deposit into abeneficiary account with the fund-availability date data elementestablished for this cash wire-transfer deposit event to determinewhether the event is compliant or non-compliant with the contractualrule.

If an event is non-compliant with the contractual rule, the cashwire-transfer deposit dollar-value data element recorded for thespecific cash wire-transfer deposit event may be divided by the totalvalue of all the cash wire-transfer deposit events with the samefunds-availability date. The resultant value for the specificnon-compliant event may then be expressed as a basis point value.Further, the total value of all non-compliant events would be divided bythe total value of all the cash wire-transfer deposit events with thesame funds-availability date. The resultant value for all non-compliantevents may then be expressed as a basis point value.

In a third example, an investment firm may wish to compare the currentvalue of the difference between its financial instrument records and thefinancial instrument records of a client's custodian bank. Eachfinancial instrument event is recorded by the investment firm and thecustodian bank, both acting for the client. At a minimum, each records agroup of data elements which include a data element equivalent to amutual client identifier; a financial instrument identifier; a financialinstrument currency identifier; a number of financial instrumentsettlement units; a financial instrument settlement value; and afinancial instrument contractual settlement date, for each event.

As of a specific contractual settlement date using the individual eventdata elements, both the investment firm and the custodian bankaccumulate the total financial instrument holdings for the client'saccount. The investment firm compares its accumulated financialinstrument holdings for the client account to the accumulated financialinstrument holdings for the same client account information obtainedfrom the custodian bank. In instances where the accumulated number offinancial instrument settlement units data elements do not match, theyare identified as non-compliant with the contractual settlement rule.The financial instrument settlement value data element of allnon-compliant financial instrument holdings is accumulated. This totalvalue of non-compliant settlement date holdings would be divided by thetotal value of all the financial instrument settlement date holdings.The resultant value for the specific non-compliant holdings would beexpressed as a basis point value.

In another example, a firm may wish to compare the current and pastoperating performance of an individual subsidiary having differentfinancial or investment objectives against other subsidiaries andagainst competitors. Utilizing metrics derived by this method, includingthe measures like those described in the prior examples, the firms havea means to compare differences in operational risks, utilizing one ormore of the methods factors, dimensions or indices that quantify theoperational risk effects, normalized to account for differences incommon industry comparison categories such as firm size, investmentstyle, automation method and process organization.

FIG. 5 shows that multiple participant firms 84 a, 84 b, and 84 c aretypically involved in assuring a financial event 88 is properlycompleted. In addition, other interested party firms 86 a, 86 b, and 86c have an interest in information about the event even though they maynot actively participate in the financial aspects of the event. Eachparticipant firm and interested party firm is exposed to some level ofoperating risk and potential financial loss based on the relationshipeach has to the event and the techniques each firm employs to collect,enter, store and utilize information about the event.

An example of the different relationships that firms have to a singleevent is an equity trade in a security listed on a registered stockexchange. The active participants include the investment manager thatdecides the security that should be purchased or sold; the broker withwhom the trade is actually completed; the exchange on which the brokerplaces the trade execution; the clearing corporation that assurestransfer of title to the securities that have been traded; the custodianthat settles the trade with the broker based on instructions from theinvestment manager; the client account in which the trade is made; andthe trust department of a local bank charged with responsibility foroversight of the finds in the client's account. The active participantsmay have operating rules in common as well as rules that are unique toeach event. Measures of process quality and risk, at any specific pointin time, can be calculated for each firm for each specific event orgroup of events by utilizing the rules that are applicable to theoperation of each individual firm.

1. A method for assessing operational process quality comprising thesteps of: identifying at least one entity which holds a legal,beneficial, contractual, regulatory or other interest in or obligationwith respect to a financial instrument and at least one metric which hassubstantial correlation to operational process quality for a preselectedoperational process of said at least one entity, wherein said metricincludes one or more factors or dimensions each of which is representedby a combination of an identifier and one or more values whichcorrespond, respectively, to one or more values of the factors ordimensions at different points in time; preselecting at least oneoperational process for quality assessment, wherein said operationalprocess comprises one or more events which follow from or are necessaryto initiate, sustain, maintain or terminate a legal, beneficial,contractual, regulatory or other interest or obligation with respect toa financial instrument; obtaining data from one or more sources whichrepresent at least one actual initial condition for said at least oneentity; continuously observing, for a preselected period of time, eventswhich relate to said at least one entity and which represent actualperformance of said preselected operational process, wherein each ofsaid events comprises an action, transaction or omission with respect toa financial instrument that affects the value of said at least oneentity; applying said metric to said data and events; processing saidmetric, using at least one processor of a computer system, to generateresults which represent a comparison of actual performance of saidoperational process with ideal performance in terms of operationalprocess quality for said at least one entity, wherein said idealperformance is defined by at least one rule and said comparisoncomprises a determination whether each of said events is compliant withsaid at least one rule, wherein said at least one rule comprises one ormore logical expressions which represent an express, implied or mandatedlegal requirement or other expectation; calculating, using said at leastone processor of said computer system, an operational value at riskbased on said generated results for said at least one entity; andexpressing substantially in real-time, using a graphical display of saidcomputer system, said calculated operational value at risk for said atleast one entity in quantitative terms, whereby a condition whichrepresents a potential loss for said at least one entity is identifiedprior to recognition of an actual loss occurring.
 2. A method forassessing operational process quality comprising the steps of: selectingat least one entity which holds a legal, beneficial, contractual,regulatory or other interest in or obligation with respect to at leastone financial instrument and at least one metric with respect to apreselected operational process of interest of said at least one entity,said at least one metric having substantial correlation to operationalprocess quality for said operational process, wherein said at least onemetric includes one or more factors or dimensions each of which isrepresented by a combination of an identifier and one or more valueswhich correspond, respectively, to one or more values of the factors ordimensions at different points in time, and wherein said preselectedoperational process comprises one or more events which follow from orare necessary to initiate, sustain, maintain or terminate a legal,beneficial, contractual, regulatory or other interest or obligation withrespect to a financial instrument; obtaining data from one or moresources which represent at least one actual initial condition for saidat least one entity; selecting event data which represent continuousobservations of the actual performance of the preselected operationalprocess of interest during a time period of interest wherein each ofsaid events comprises an action, transaction or omission with respect tosaid at least one financial instrument that affects the value of said atleast one entity; applying, using at least one processor of a computersystem, one or more process metrics and rules, which represent idealperformance of the operational process of interest in terms of quality,to the selected event data to produce intermediate results, wherein theintermediate results represent a comparison of actual performance ofsaid operational process with ideal performance in terms of operationalprocess quality for said at least one entity, wherein said idealperformance is defined by at least one rule and said comparisoncomprises a determination whether each of said events is compliant withsaid at least one rule, wherein said at least one rule comprises one ormore logical expressions which represent an express, implied or mandatedlegal requirement or other expectation, wherein said at least oneprocess measure comprises one or more logical expressions used tocalculate operational process quality; and applying the selected metricto said intermediate results, using said at least one processor of acomputer system, to calculate an operational value at risk inquantitative terms, whereby a condition which represents a potentialloss for said at least one entity is identified prior to recognition ofan actual loss occurring.
 3. A computer readable medium, includingprogram instructions executing on at least one processor of a computer,the computer readable medium including program instructions for a methodfor assessing operational process quality comprising: providing a datastore, using a computer memory or computer data storage device, whichcontains data pertaining to at least one entity which holds a legal,beneficial, contractual, regulatory or other interest in or obligationwith respect to at least one financial instrument and one or more eventswhich represent continuous observations of the actual performance of apreselected operational process of interest, wherein each of said eventscomprises an action, transaction or omission with respect to said atleast one financial instrument that affects the value of said at leastone entity and data from one or more sources which represent at leastone actual initial condition for said at least one entity; providing aprocess measures and rules store, using said computer memory or computerdata storage device, which contains at least one process measure and atleast one rule pertaining to said preselected operational process ofinterest; applying, using at least one processor of a computer system,said at least one process measure and at least one rule to selected datafrom said data store to generate intermediate results which represent acomparison of actual performance of said preselected operational processwith ideal performance in terms of operational process quality for saidat least one entity, wherein said ideal performance is defined by atleast one rule and said comparison comprises a determination whethereach of said events is compliant with said at least one rule, whereinsaid at least one rule comprises one or more logical expressions whichrepresent an express, implied or mandated legal requirement or otherexpectation; providing a metric store, using said computer memory orcomputer data storage device, which contains at least one metric havingsubstantial correlation to operational process quality for saidoperational process of interest, wherein said at least one metricincludes one or more factors or dimensions each of which is representedby a combination of an identifier and one or more values whichcorrespond, respectively, to one or more values of the factors ordimensions at different points in time; applying said at least onemetric to said intermediate results to calculate, using said at leastone processor of a computer system, an operational value at risk forsaid at least one entity; and expressing substantially in real-time,using a graphical display of said computer system, said calculatedoperational value at risk in quantitative terms, whereby a conditionwhich represents a potential loss for said at least one entity isidentified prior to recognition of an actual loss occurring.
 4. Acomputer system for assessing operational process quality comprising: atleast one computer memory or computer data storage device comprising adata store for data which is related to at least one entity which holdsa legal, beneficial, contractual, regulatory or other interest in orobligation with respect to at least one financial instrument and one ormore events which represent continuous observations of the actualperformance of a preselected operational process, wherein each eventcomprises an action, transaction or omission with respect to said atleast one financial instrument that affects the value of said at leastone entity and data from one or more sources which represent at leastone actual initial condition for said at least one entity; said at leastone computer memory or computer data storage device further comprising aprocess measures and rules store, coupled in communicating relationshipwith said data store, for applying at least one process measure and atleast one rule to selected data of interest in said data store toproduce intermediate results which represent a comparison of actualperformance of said operational process with ideal performance in termsof operational process quality for said at least one entity, whereinsaid ideal performance is defined by at least one rule and saidcomparison comprises a determination whether each of said events iscompliant with said at least one rule, wherein said at least one rulecomprises one or more logical expressions which represent an express,implied or mandated legal requirement or other expectation; said atleast one computer memory or computer data storage device furthercomprising a metric store, coupled in communicating relationship withsaid process measures and rules store, for receiving said intermediateresults and applying a selected metric to said intermediate results tocalculate an operational value at risk for said at least one entityexpressed in quantitative terms, said metric having substantialcorrelation to operational process quality for an operational process ofinterest, wherein said metric includes one or more factors or dimensionseach of which is represented by a combination of an identifier and oneor more values which correspond, respectively, to one or more values ofthe factors or dimensions at different points in time; and a userinterface, coupled in communicating relationship with said metric store,for enabling a user to select one or more metrics of interest and todisplay said calculated operational value at risk, whereby a conditionwhich represents a potential loss for said at least one entity isidentified prior to recognition of an actual loss occurring.
 5. Acomputer system for assessing operational process quality comprising: atleast one computer memory or computer data storage device comprising afirst store containing at least one metric pertaining to an operationalprocess of interest, said at least one metric having substantialcorrelation to operational process quality for said operational processof interest, wherein said at least one metric includes one or morefactors or dimensions each of which is represented by a combination ofan identifier and one or more values which correspond, respectively, toone or more values of the factors or dimensions at different points intime; said at least one computer memory or computer data storage devicefurther comprising a second store containing observed event data whichrepresent actual performance of the operational process of interestduring a time period of interest; said at least one computer memory orcomputer data storage device further comprising a third store, coupledin communicating relationship with said second store, containing one ormore process measures and rules which represent ideal performance of theoperational process of interest in terms of quality; a processor forapplying said one or more process measures and rules to selected eventdata to generate intermediate results and applying said at least onemetric to said intermediate results to calculate an operational value atrisk wherein the intermediate results represent a comparison of actualperformance of said operational process with ideal performance in termsof operational process quality for said at least one entity, whereinsaid ideal performance is defined by at least one rule and saidcomparison comprises a determination whether each of said events iscompliant with said at least one rule, wherein said at least one rulecomprises one or more logical expressions which represent an express,implied or mandated legal requirement or other expectationl; and a userinterface, coupled in communicating relationship with said first store,for enabling a user to select one or more metrics of interest and todisplay said calculated operational value at risk, whereby a conditionwhich represents a potential loss for said at least one entity isidentified prior to recognition of an actual loss occurring.
 6. Acomputer system for assessing operational process quality comprising: atleast one computer memory or computer data storage device comprising afirst store containing at least one metric which has substantialcorrelation to operational process quality for a preselected operationalprocess, wherein said at least one metric includes one or more factorsor dimensions each of which is represented by a combination of anidentifier and one or more values which correspond, respectively, to oneor more values of the factors or dimensions at different points in time;said at least one computer memory or computer data storage devicecomprising a second store, coupled in communicating relationship withsaid first store, containing event data received from one or moresources which represent actual performance of said preselectedoperational process for at least one entity which holds a legal,beneficial, contractual, regulatory or other interest in or obligationwith respect to at least one financial instrument; a processor forprocessing said metric using selected event data from said second storeto generate results which represent a comparison of actual performanceof said operational process with ideal performance in terms ofoperational process quality or risk, wherein said ideal performance isdefined by at least one rule and said comparison comprises adetermination whether each of one or more events is compliant with saidat least one rule, wherein said at least one rule comprises one or morelogical expressions which represent an express, implied or mandatedlegal requirement or other expectation; calculating an operational valueat risk based on said generated results; and a user interface forexpressing substantially in real-time said calculated operational valueat risk in quantitative terms, whereby a condition which represents apotential loss for said at least one entity is identified prior torecognition of an actual loss occurring.
 7. A method for assessingoperational process quality comprising the steps of: identifying aplurality of entities each of which holds a legal, beneficial,contractual, regulatory or other interest in or obligation with respectto a financial instrument; preselecting at least one operational processfor quality assessment; identifying, for said at least one operationalprocess, at least one metric which has substantial correlation tooperational process quality for said preselected at least oneoperational process, wherein said at least one metric includes one ormore factors or dimensions each of which is represented by a combinationof an identifier and one or more values which correspond, respectively,to one or more values of the factors or dimensions at different pointsin time; obtaining data from one or more sources which represent atleast one actual initial condition for each of said entities;continuously observing, for a preselected period of time, events whichrelate to all of said entities and which represent actual performance ofsaid preselected operational process, wherein each of said eventscomprises an action, transaction or omission with respect to saidfinancial instrument that affects the value of all of said entities;applying said metric to said data and events; processing said at leastone metric, using at least one processor of a computer system, togenerate results which represent a comparison of actual performance ofsaid operational process with ideal performance in terms of operationalprocess quality or risk for each of said entities, wherein said idealperformance is defined by at least one rule and said comparisoncomprises a determination whether each of said events is compliant withsaid at least one rule, wherein said at least one rule comprises one ormore logical expressions which represent an express, implied or mandatedlegal requirement or other expectation; calculating, using said at leastone processor of said computer system, an operational value at risk foreach of said entities based on said generated results; and expressingsubstantially in real-time, using a graphical display of said computersystem, said calculated operational value at risk for at least one ofsaid entities in quantitative terms, whereby a condition whichrepresents a potential loss for said at least one entity is identifiedprior to recognition of an actual loss occurring.
 8. The method as inclaim 1, 2, 3 or 7 wherein said quantitative terms comprises basispoints.
 9. The method as in claim 1, 2, 3 or 7 wherein an event isrepresented by a combination of an event identifier, an entityidentifier, a financial instrument identifier, one or more expectedconditions, one or more actual conditions, a value and a category. 10.The method as in claim 1, 2, 3 or 7 wherein said rule is represented bya combination of a rule identifier, an entity identifier, an instrumentidentifier, a rule type and one or more conditions.
 11. The method as inclaim 1, 2, 3 or 10 wherein said method is used to assess theoperational process quality associated with failing to comply withregulatory, contractual or other expectations attached to transactionsinvolving one or more financial instruments.
 12. The method as in claim1, 2, 3 or 10 wherein said method is used to compare performances, interms of operational quality, of two or more business organizations. 13.The method as in claim 1, 2, 3 or 7 wherein said method is used tomeasure and attribute operations performance.
 14. The method as in claim1, 2, 3 or 7 wherein said method is used to identify and prioritizeoperational and system improvement opportunities.
 15. The method as inclaim 1, 2, 3 or 7 wherein said method is used to calculate operatingrisk capital allocations or reserves to establish premiums or benchmarksfor insurance underwriting purposes.
 16. The method as in claim 1, 2, 3or 7 wherein said method is used to distribute performance-basedcompensation.
 17. The method as in claim 1, 2, 3 or 10 wherein saidquantitative terms are calculated using a total value of the legal,beneficial, contractual, regulatory or other interest or obligation of arespective entity.